Even if the data are distributed normally, nonparametric methods are often almost as powerful as parametric methods. Most nonparametric methods are based on taking the ranks of a variable and ...

Under stronger conditions, a consistent nonparametric estimator of the drift function is also derived based on the diffusion function estimator and the marginal density of the process. An application ...

Four new nonparametric estimators of static CoVaR are proposed. They are shown to be consistent and asymptotically normal under random sampling. Their performance is compared in simulation studies.

We develop nonparametric smoothing for regression when both the predictor and the response variables are defined on a sphere of whatever dimension. A local polynomial fitting approach is pursued, ...

This paper designs a Bayesian nonparametric covariance estimator by integrating the pooling method, vector moving average adjustment and synchronization with data augmentation. The proposed covariance ...

The conventional growth-accounting approach to estimating the sources of economic growth requires unrealistically strong assumptions about the competitiveness of factor markets and the form of the ...